Comprehensive Analysis of Student Performance & Behavior Using Python

In this project, I conducted an in-depth analysis of student performance using a dataset containing 5,000 student records with 23 academic and demographic variables. The goal was to uncover key factors influencing student success, such as attendance rates, study habits, stress levels, and extracurricular activities.

Key Highlights:

Data Cleaning & Preprocessing.

Exploratory Data Analysis (EDA).

Performance Correlation Analysis.

Gender & Department-Wise Comparisons.

Data-Driven Recommendations.